Evaluation of sensor, environment and operational factors impacting the use of multiple sensor constellations for long term resource monitoring

DIRS Lab 76-3215

July 12, 2016 at 10:00am

Rajagopalan Rengarajan

PhD Thesis Defense

Abstract:

Abstract

Moderate resolution remote sensing data oﬀers the potential to monitor the long and short term trends in the condition of the Earth’s resources atﬁner spatial scales and over longer time periods. While improved calibration (radiometric and geometric), free access (Landsat, Sentinel, CBERS), and higher level products in reﬂectance units have made it easier for the science community to derive the biophysical parameters from these remotely sensed data, a number of issues still aﬀect the analysis of multi-temporal datasets. These are primarily due to sources that are inherent in the process of imaging from single or multiple sensors. Some of these undesired or uncompensated sources of variation include variation in the view angles, illumination angles, atmospheric eﬀects, and sensor eﬀects such as Relative Spectral Response (RSR) variation between diﬀerent sensors. The complex interaction of these sources of variation would make their study extremely diﬃcult if not impossible with real data, and therefore, a simulated analysis approach is used in this study.

A synthetic forest canopy is produced using the Digital Imaging and Remote Sensing Image Generation (DIRSIG) model and its measured BRDFs are modeled using the RossLi canopy BRDF model. The simulated BRDF matches the real data to within 2% of the reﬂectance in both the red and the NIR spectral bands. The BRDF modeling process is extended to model and characterize the defoliation of a forest, which is used in factor sensitivity studies to estimate the eﬀect of each factor for varying environment and sensor conditions. Finally, a factorial experiment is designed to understand the signiﬁcance of the sources of variation, and regression based analysis are performed to understand the relative importance of the factors. The design of experiment and the sensitivity analysis conclude that the atmospheric attenuation and variations due to the illumination angles are the dominant sources impacting the at-sensor radiance.